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...ow.. histogram(~factor(sample(letters,200,rep=T))) I was able to get it in 3 - 4 steps.. l a1 <- sample(letter,200,rep=T) a2 <- table(a1) barplot(a2); barplot(sort(a2)) # all variables are not displayed on the x-axis in the barplot histogram(factor(a1)) # the resulting bars are not shown in seqentially increasing or decreasing order how do I use similar plots if I have data.frame... example is shown below.. b1 <- data.frame(lets=sample(letters,200,rep=T),n=seq(200)) barplot(sort(table(b1$lets)) histogram(b1$lets) Regards, Santosh [[alternative HTML version deleted]]

...commended method for pre-condensing the data before inputting them into aov in R? I want to be able to preserve the person factor (42) for further analysis. I could try to aggregate the response variables for all and use a count for weighting them. AFAIS, in principle the cases could be submitted seqentially to the fitting process avoiding the explicit building of the model matrix. Is anybody working on this in R context? -- Dipl.-Math. Wilhelm Bernhard Kloke Institut fuer Arbeitsphysiologie an der Universitaet Dortmund Ardeystrasse 67, D-44139 Dortmund, Tel. 0231-1084-257 -.-.-.-.-.-.-.-.-.-.-.-....

Hi. bash-3.00# uname -a SunOS nfs-14-2.srv 5.10 Generic_125101-03 i86pc i386 i86pc I created first zpool (stripe of 85 disks) and did some simple stress testing - everything seems almost alright (~700MB seq reads, ~430 seqential writes). Then I destroyed pool and put SVM stripe on top the same disks utilizing the fact that zfs already put EFI and s0 represents almost entire disk. The on top on SVM volume I put zfs and simple dd files, then zpool scrub and: bash-3.00# zpool status test pool: test state: ONLINE status...